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DESCRIPTION

@@ -1,6 +1,6 @@
 Package: lczexplore
 Title: lczexplore
-Version: 0.0.1.0002
+Version: 0.0.1.0003
 Authors@R: c(
     person("Matthieu", "Gousseff", , "[email protected]", role = c("aut", "cre")),
     person(, "Centre National de la Recherche Scientifique, Lab-Sticc", role = "cph", comment = c(ORCID = "0000-0002-7106-2677"))

docs/articles/joss/paper.bib

@@ -256,7 +256,8 @@ @article{demuzere2022global
   volume={2022},
   pages={1--57},
   year={2022},
-  publisher={G{\"o}ttingen, Germany}
+  publisher={G{\"o}ttingen, Germany},
+  doi = {10.5194/ems2022-83}
 }
 
 @article{demuzere2020combining,
@@ -267,5 +268,6 @@ @article{demuzere2020combining
   number={1},
   pages={264},
   year={2020},
-  publisher={Nature Publishing Group UK London}
+  publisher={Nature Publishing Group UK London},
+  doi = {10.1038/s41597-020-00605-z}
 }

docs/articles/joss/paper.md

@@ -244,6 +244,8 @@ One can then feed `compareLCZ` function these new groups,  setting `repr="alter"
 
 ### Import and explore categorical variable (other than LCZ classifications)
 
+This package focuses on LCZ maps comparison, but more often than not, people working on LCZ maps also 
+describe their area of interest with other categorical indicators. 
 The workflow of comparison of LCZ maps can be used for any pair of maps of categorical variables,
 under certain limitations:
 - there must not be more than 36 levels for the categorical variable to explore
@@ -354,7 +356,7 @@ deals with standard values of LCZ levels and colors.
 
 # Plot the LCZ levels on the Redon Area using the default color set
 # from the sf object produced by importLCZvect function
-showLCZ(
+map1<-showLCZ(
   sf=redonOSM, column="LCZ_PRIMARY", repr="standard",
   title="LCZ Classification on the French City of Redon")
 
@@ -519,7 +521,7 @@ It is the possible to perform the same analysis as on standard LCZ classificatio
 as shown in the following example:
 
 ```r
-showLCZ(redonOSMgrouped, column="grouped",repr="alter",
+map2<-showLCZ(redonOSMgrouped, column="grouped",repr="alter",
         title="Regrouped Categories for the city of Redon",
         LCZlevels = c("urban","industry","vegetation","impervious","pervious","water"),  
         colors=c("red","black","green","grey","burlywood","blue"))
@@ -548,7 +550,7 @@ utrfRedonBDT<-importQualVar(dirPath=paste0(
   system.file("extdata", package = "lczexplore"), "/bdtopo_2_2/Redon"),
   file="rsu_utrf_area.geojson", column="TYPO_MAJ")
 
-showLCZ(sf=utrfRedonBDT, column="TYPO_MAJ",repr="alter", 
+map3<-showLCZ(sf=utrfRedonBDT, column="TYPO_MAJ",repr="alter", 
         title = " UTRF classification of the French city of Redon")
 ```
 ![An example of some qualitative variable: Urban Typology by Random Forest (UTRF)](importQualVarUTRF.png)

inst/tinytest/test_importLCZraster.R

@@ -28,14 +28,66 @@ upCorner<-st_point(c(-117.227554,32.864593))
 outBbox<-st_sfc(lowCorner,upCorner,crs=4326)
 #importLCZraster("/home/gousseff/Documents/2_CodesSources/Wudapt/WudaptEurope/",bBox=outBbox)
 
-
+# test bounding box not intersecting with rastet
 expect_error(current = test<-importLCZraster(dirPath = system.file("extdata", package = "lczexplore"),fileName="redonWudapt.tif",bBox=outBbox),
              "The bounding box doesn\'t intersect ")
 
 
+# test chosing wich band of the raster is imported
 redonWudapt2<-importLCZraster(  
   system.file("extdata", package = "lczexplore"),
   fileName="redonWudapt.tif",bBox=redonBbox,
 LCZband=1, LCZcolumn="LCZ")
  str(redonWudapt2)
 
+sidneyOSM<-importLCZvect(
+  dirPath = system.file("extdata/osm/2022/Sidney", package = "lczexplore"), file="sidney_rsu_lcz.geojson",
+  confid="LCZ_UNIQUENESS_VALUE",
+  geomID="ID_RSU")
+
+sidneyBbox<-importLCZvect(
+  system.file("extdata/osm/2022/Sidney", package = "lczexplore"), file="sidney_rsu_lcz.geojson",
+  ,output = "bBox")
+
+# test default import
+
+expect_warning(sidneyWudapt<-importLCZraster(system.file("extdata", package = "lczexplore"),
+                              fileName="rasterMD.tif",bBox=sidneyBbox),
+               "attribute variables are assumed to be spatially constant throughout all geometries")
+
+# test default specifying band number
+
+expect_warning(sidneyWudapt<-importLCZraster(system.file("extdata", package = "lczexplore"),
+                             fileName="redonWudapt.tif",bBox=redonBbox, LCZband=1, LCZcolumn='EU_LCZ_map'),
+               "attribute variables are assumed to be spatially constant throughout all geometries")
+
+
+expect_error(sidneyWudapt<-importLCZraster(system.file("extdata", package = "lczexplore"),
+                              fileName="redonWudapt.tif",bBox=redonBbox, LCZband=4, LCZcolumn='EU_LCZ_map'),
+             "invalid name")
+
+# test importing a band that doesn't exist (wrong name)
+expect_error(sidneyWudapt<-importLCZraster(system.file("extdata", package = "lczexplore"),
+                                           fileName="redonWudapt.tif",bBox=redonBbox, LCZband="Ski shoe", LCZcolumn='EU_LCZ_map'),
+             "invalid name")
+
+# test importing several bands of the raster is imported, one being the confidence, one being numeric and the other the name of a band
+
+expect_warning(sidneyWudapt<-importLCZraster(system.file("extdata", package = "lczexplore"),
+                fileName="rasterMD.tif", LCZband=1,  LCZcolumn = "LCZraster",
+                confidenceBand = 3, confidenceColumn = "confidence",
+                bBox = sidneyBbox ),
+               "attribute variables are assumed to be spatially constant")
+
+expect_warning(sidneyWudapt<-importLCZraster(system.file("extdata", package = "lczexplore"),
+                                             fileName="rasterMD.tif", LCZband="lcz",  LCZcolumn = "LCZraster",
+                                             confidenceBand = 3, confidenceColumn = "confidence",
+                                             bBox = sidneyBbox ),
+               "attribute variables are assumed to be spatially constant")
+
+# test importing several bands, one being wrong
+
+expect_error(sidneyWudapt<-importLCZraster(system.file("extdata", package = "lczexplore"),
+                                           fileName="rasterMD.tif",bBox=sidneyBbox, LCZband=1, LCZcolumn='EU_LCZ_map',
+                                           confidenceBand = "skishoe", confidenceColumn = "confidence"),
+             "invalid name")

vignettes/lczexplore_alter.Rmd

@@ -95,7 +95,7 @@ redonOSMgrouped<-groupLCZ(redonOSM,column="LCZ_PRIMARY",
 levCol(sf=redonOSMgrouped,column="grouped",LCZlevels = c("urban","industry","vegetation","impervious","pervious","water"),
        colors=c("red","black","green","grey","burlywood","blue"))
 
-showLCZ(redonOSMgrouped, column="grouped",repr="alter",wf="OSM",
+map1<-showLCZ(redonOSMgrouped, column="grouped",repr="alter",wf="OSM",
         LCZlevels = c("urban","industry","vegetation","impervious","pervious","water"),
         colors=c("red","black","green","grey","burlywood","blue"))
 
@@ -168,7 +168,7 @@ utrfRedonBDT<-importQualVar(dirPath=paste0(
 summary(utrfRedonBDT)
 summary(utrfRedonBDT$TYPO_MAJ)
 
-showLCZ(sf=utrfRedonBDT, column="TYPO_MAJ",repr="alter",
+map3<-showLCZ(sf=utrfRedonBDT, column="TYPO_MAJ",repr="alter",
         title = " UTRF classification of the French city of Redon",
         colors=c("red","black","green","grey","burlywood","blue","orange","lightgreen","brown"))
 ```
@@ -231,7 +231,7 @@ If the values of the grouping vectors cover the original values of the datasets,
 
 ```{R, fig.dim = c(8, 6), echo = TRUE}
 
-showLCZ(sf=redonBDT, column="LCZ_PRIMARY", repr="alter",
+map4<-showLCZ(sf=redonBDT, column="LCZ_PRIMARY", repr="alter",
         urban=c("1","2","3","4","5","6","7","8","9"),
         industry="10",
         vegetation=c("101","102","103","104"),
@@ -250,5 +250,5 @@ compareLCZ(sf1=redonBDT, column1="LCZ_PRIMARY",
 ```
 This is meant as an exploratory tool, as the resulting grouped columns are not actually kept after the analysis. 
 
-Please feel free to contact us if some case are not handled by the package. 
+Please feel free to contact us if some cases are not handled by the package. 
 

vignettes/lczexplore_fr.Rmd

@@ -92,7 +92,7 @@ L'argument `repr=standard` (valeur par défaut), permet de gérer les niveaux de
 des cartes mises en forme avec des couleurs standardisées.
 
 ```{r, echo=FALSE, fig.dim = c(8, 6)}
-showLCZ(sf=redonOSM, wf="OSM", column="LCZ_PRIMARY", repr="standard")
+map1<-showLCZ(sf=redonOSM, wf="OSM", column="LCZ_PRIMARY", repr="standard")
 ```
 
 On remarque que par défaut, tous les niveaux attendus d'une classification LCZ sont présents, ce qui peut faciliter l'exploration
@@ -101,7 +101,7 @@ Si on souhaite ne représenter que les niveaux présents dans les données, il s
 niveaux absents ne seront pas représentés. 
 
 ```{r, fig.dim = c(8, 6), echo = FALSE}
-showLCZ(sf=redonOSM,wf="OSM",column="LCZ_PRIMARY",repr="standard",drop=TRUE)
+map2<-showLCZ(sf=redonOSM,wf="OSM",column="LCZ_PRIMARY",repr="standard",drop=TRUE)
 ```
 
 
@@ -123,7 +123,7 @@ et les niveaux déduits des valeurs présentes.
 ```{r, fig.dim = c(8, 6), echo = FALSE}
 # Choix d'un vecteur de couleurs alternatif aléatoire
 testCol <- palette.colors(n=17, palette="Polychrome 36")
-showLCZ(sf=redonOSM,wf="OSM",column="LCZ_PRIMARY",repr="alter",colors=testCol, useStandCol = FALSE)
+map3<-showLCZ(sf=redonOSM,wf="OSM",column="LCZ_PRIMARY",repr="alter",colors=testCol, useStandCol = FALSE)
 
 ```
 
@@ -135,7 +135,7 @@ qui n'est pas présent dans les données, et on laisse la fonction choisir des c
 ```{r, fig.dim = c(8, 6), echo = FALSE}
 
 LCZlevels<-c(2, 3, 5, 6, 8, 9, 10, 101, 102, 104, 105, 107)
-showLCZ(sf=redonOSM,wf="OSM",column="LCZ_PRIMARY",repr="alter", LCZlevels = LCZlevels,drop=FALSE)
+map4<-showLCZ(sf=redonOSM,wf="OSM",column="LCZ_PRIMARY",repr="alter", LCZlevels = LCZlevels,drop=FALSE)
 ```
 
 On peut également renseigner le vecteur des couleurs qu'on souhaite utiliser en renseignant l'argument`colors`.
@@ -149,7 +149,7 @@ On peut renseigner les noms de couleurs connues de R ou un code RGB.
 LCZlevels<-c(2, 3, 5, 6, 8, 9, 101, 102, 104, 105, 107)
 couleurs<-c("red","brown1","orange","coral","grey","darkgreen","chartreuse4","springgreen3",
             "darkolivegreen","black","#6d67fd")
-showLCZ(sf=redonOSM,wf="OSM",column="LCZ_PRIMARY",repr="alter",drop=TRUE,LCZlevels=LCZlevels,colors=couleurs)
+map5<-showLCZ(sf=redonOSM,wf="OSM",column="LCZ_PRIMARY",repr="alter",drop=TRUE,LCZlevels=LCZlevels,colors=couleurs)
 
 ```
 
@@ -175,7 +175,7 @@ redonOSMgrouped<-groupLCZ(redonOSM,column="LCZ_PRIMARY",
                            industry="10",
                            vegetation=c("101","102","103","104"),
                            impervious="105",pervious="106",water="107",colors=c("red","black","green","grey","burlywood","blue"))
-showLCZ(redonOSMgrouped, column="grouped",repr="alter",wf="OSM",
+map6<-showLCZ(redonOSMgrouped, column="grouped",repr="alter",wf="OSM",
         LCZlevels = c("urban","industry","vegetation","impervious","pervious","water"),
         colors=c("red","black","green","grey","burlywood","blue"))
 

vignettes/lczexplore_raster_vector.Rmd

@@ -95,7 +95,7 @@ For standard LCZ types, one sets the argument `repr="standard"`, and the functio
 
 
 ```{r, fig.dim = c(8, 6)}
-showLCZ(sf = redonWudapt,column = 'EU_LCZ_map', repr= "standard")
+map1<-showLCZ(sf = redonWudapt,column = 'EU_LCZ_map', repr= "standard")
 ```
 
 
@@ -119,8 +119,8 @@ summary(redonOSM$LCZ_PRIMARY)
 ```
 ## Visualize the resulting LCZ types with the function showLCZ
 The resulting object is an sf object and can therefore also be visualized with the showLCZ function.
-```{r, echo = TRUE }
-showLCZ(sf = redonOSM, repr="standard")
+```{r, fig.dim = c(8, 6), echo = TRUE }
+map2<-showLCZ(sf = redonOSM, repr="standard")
 
 ```